Not sure if you are aware of the OpenMx SEM package
(http://openmx.psyc.virginia.edu/). It's a very full-featured structural
equation modeling package.
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I am trying to use the cfa command in the lavaan package to run a CFA
however I am unsure over a couple of issues.
I have @25 dichotomous variables, 300 observations and an EFA on a
training dataset suggests a 3 factor model.
That is a lot of variables, and a rather small sample size (for binar
> Cc: r-help@R-project.org
> Subject: Re: [R] CFA with lavaan or with SEM
>
. . .
>
> model.1 <- specifyEquations()
> f1 = gam11*a + gam12*b + gam13*c + gam14*d + gam15*e + gam16*g
> f1 = 1* f1
>
First, this is backwards: the observed variables depend on the fact
n eval(expr, envir, enclos) :
Could not compute QR decomposition of Hessian.
Optimization probably did not converge.
-- snip ---
The problem seems ill-conditioned, and in any event the standard errors that
you get using tetrachoric correlations won't be right (I expect you kn
y grateful if you could indicate where the error in my code is
please.
thanks, david
-Original Message-
From: John Fox [mailto:j...@mcmaster.ca]
Sent: 23 January 2013 14:00
To: David Purves
Cc: r-help@R-project.org
Subject: Re: [R] CFA with lavaan or with SEM
Dear David,
On Wed,
Dear David,
On Wed, 23 Jan 2013 11:19:09 +
David Purves wrote:
> Hi
>
> Sorry for the rather long message.
>
. . .
>
> I have tried the analysis using John Fox's SEM package / command.
>
> I calculate the correlation matrix with smoothing
>
> my.cor<-hetcor(north.dat.sub,use="pairwise
Hi
Sorry for the rather long message.
I am trying to use the cfa command in the lavaan package to run a CFA however I
am unsure over a couple of issues.
I have @25 dichotomous variables, 300 observations and an EFA on a training
dataset suggests a 3 factor model.
After defining the model I us
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